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Advanced inventory management system FULL SOURCE CODE FREE 👇
https://inprogrammer.com/inventory-management-using-python/
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🔥 Master These 30 Algorithms to Boost Your Coding Skills! 🚀
- Binary Search 🕵️♂️
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- Prim’s Algorithm 🌿
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- Backtracking 🎯
- Binary Tree Traversals 🌳
- Segment Tree 📊
- Union-Find Disjoint Set 🔗
- Greedy Algorithms 🎯
- Bit Manipulation 💡
- Sliding Window ⏱️
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Master these, ace interviews, and become a problem-solving pro! 💪🔥
***
53 · 8.8K · Фотографія
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🚀 𝗕𝗲𝗰𝗼𝗺𝗲 𝗮𝗻 𝗔𝗜/𝗟𝗟𝗠 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿: 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗣𝗿𝗼𝗴𝗿𝗮𝗺
𝗠𝗮𝘀𝘁𝗲𝗿 𝘁𝗵𝗲 𝘀𝗸𝗶𝗹𝗹𝘀 𝘁𝗲𝗰𝗵 𝗰𝗼𝗺𝗽𝗮𝗻𝗶𝗲𝘀 𝗮𝗿𝗲 𝗵𝗶𝗿𝗶𝗻𝗴 𝗳𝗼𝗿: fine-tune large language models and deploy them to production at scale.
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7 · 7.4K · Codehub
✅Python Interview Questions with Answers 🧑💻👩💻
1️⃣ Write a function to remove outliers from a list using IQR.
import numpy as np
def remove_outliers(data):
q1 = np.percentile(data, 25)
q3 = np.percentile(data, 75)
iqr = q3 - q1
lower = q1 - 1.5 * iqr
upper = q3 + 1.5 * iqr
return [x for x in data if lower <= x <= upper]
2️⃣ Convert a nested list to a flat list.
nested = [[1, 2], [3, 4],]
flat = [item for sublist in nested for item in sublist]
3️⃣ Read a CSV file and count rows with nulls.
import pandas as pd
df = pd.read_csv('data.csv')
null_rows = df.isnull().any(axis=1).sum()
print("Rows with nulls:", null_rows)
4️⃣ How do you handle missing data in pandas?
⦁ Drop missing rows: df.dropna()
⦁ Fill missing values: df.fillna(value)
⦁ Check missing data: df.isnull().sum()
5️⃣ Explain the difference between loc[] and iloc[].
⦁ loc[]: Label-based indexing (e.g., row/column names)
Example: df.loc[0, 'Name']
⦁ iloc[]: Position-based indexing (e.g., row/column numbers)
Example: df.iloc
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14 · 7.2K · ✅Python Interview Questions with Answers 🧑💻👩💻
1️⃣ Write a function to remove outliers from a list using IQR.
import numpy as np
def remove_outliers(data):
q1 = np.percentile(data, 25)
q3 = np.percentile(data, 75)
iqr = q3 - q1
lower = q1 - 1.5 * iqr
upper = q3 + 1.5 * iqr
return [x for x in data if lower <= x <= upper]
2️⃣ Convert a nested list to a flat list.
nested = [[1, 2], [3, 4],]
flat = [item for sublist in nested for item in sublist]
3️⃣ Read a CSV file and count rows with nulls.
import pandas as pd
df = pd.read_csv('data.csv')
null_rows = df.isnull().any(axis=1).sum()
print("Rows with nulls:", null_rows)
4️⃣ How do you handle missing data in pandas?
⦁ Drop missing rows: df.dropna()
⦁ Fill missing values: df.fillna(value)
⦁ Check missing data: df.isnull().sum()
5️⃣ Explain the difference between loc[] and iloc[].
⦁ loc[]: Label-based indexing (e.g., row/column names)
Example: df.loc[0, 'Name']
⦁ iloc[]: Position-based indexing (e.g., row/column numbers)
Example: df.iloc
💬 Tap ❤️ for more!
10 · 9K · Codehub
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3 · 7.2K · Codehub
✅ *Python Scenario-Based Interview Question* 🧠🐍
You have a list: numbers = [1, 2, 3, 2, 4, 1, 5, 2]
*Question:*
Find the number that appears most frequently in the list.
*Expected Output:* 2
*Python Code:* from collections import Counter
most_common_num = Counter(numbers).most_common(1)[0][0]
print(most_common_num)
*Explanation:*
– Counter() counts occurrences of each element
– most_common(1) returns the most frequent item
– Access [0][0] to get just the number
💬 *Tap ❤️ for more bite-sized Python tips!*
***
Would you like the next one to be slightly more advanced (e.g., involving strings or list comprehensions)?
7 · 8.5K · Codehub
💡 25 VS Code Extensions Every Dev Should Try 💻
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🔥 React “❤️” if you use VS Code daily!
43 · 9.7K · Codehub
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Top 50 Data Analyst Interview Questions (2025) 🎯📊
1. What does a data analyst do?
2. Difference between data analyst, data scientist, and data engineer.
3. What are the key skills every data analyst must have?
4. Explain the data analysis process.
5. What is data wrangling or data cleaning?
6. How do you handle missing values?
7. What is the difference between structured and unstructured data?
8. How do you remove duplicates in a dataset?
9. What are the most common data types in Python or SQL?
10. What is the difference between INNER JOIN and LEFT JOIN?
11. Explain the concept of normalization in databases.
12. What are measures of central tendency?
13. What is standard deviation and why is it important?
14. Difference between variance and covariance.
15. What are outliers and how do you treat them?
16. What is hypothesis testing?
17. Explain p-value in simple terms.
18. What is correlation vs. causation?
19. How do you explain insights from a dashboard to non-technical stakeholders?
20. What tools do you use for data visualization?
21. Difference between Tableau and Power BI.
22. What is a pivot table?
23. How do you build a dashboard from scratch?
49. What do you do if data contradicts business intuition?
50. What are your favorite analytics tools and why?
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💬 Tap ❤️ for the detailed answers!
27 · 14.7K · Codehub
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python interview question with answer.pdf · 6 КБ · натисніть — покажемо
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python interview question with answer.pdf
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🚀 Python & AI related amazing articles daily on Medium!
💻 Latest Topic:
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4 · 7.8K · Відповідь🚀 Python & AI related amazing articles daily on Medium!
💻 Latest Topic:
“ I Built the Same AI Agent in 4 Python Frameworks. One Was Clearly Better.
🚀”
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4 · 7.3K · Codehub
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🔥 The AI Trick That Got 4 Interview Calls Without Applying to Hundreds of Jobs
Everyone is talking about AI. Very few people are using it to get hired.
This case study shows exactly how one person used AI to stand out from thousands of applicants.
👇 Read Here“ by The AI Coder on Medium: https://medium.com/@vaishnavi.singh0324/how-one-ai-tool-helped-me-get-4-interview-calls-in-30-days-without-applying-to-hundreds-of-jobs-e362f4bb5190
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7 · 8.1K · Codehub
FREE 50$ Claude Code Api Grab It And Build Your AI Apps No NEED TO PAY FOR CLAUDE CODE HERE IS THE LINK https://agentrouter.org/register?aff=JiVL
4 · 3.5K · Codehub
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Redeem my code in Settings within 48 hours of joining and we'll both get 1 billion Muse tokens.
Code: EKSFKE
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